Efficient Hybrid Attention: KL-Guided Layer Selection for Model Distillation
Published:Dec 23, 2025 18:12
•1 min read
•ArXiv
Analysis
This research explores a method to optimize hybrid attention models through knowledge distillation, focusing on layer selection guided by the Kullback-Leibler divergence. The approach potentially leads to more efficient models while preserving performance, which is valuable for resource-constrained applications.
Key Takeaways
Reference
“The research focuses on KL-guided layer selection.”